In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
The "download first, then process paradigm" is still the predominant working method amongst the research community. The web-based paradigm, however, offers many advantag...
Marc Kemps-Snijders, Alexander Klassmann, Claus Zi...
—Workload characterisation and generation is becoming an increasingly important area as hardware and application complexities continue to advance. In this paper, we introduce a c...
The Singular Value Decomposition is a key operation in many machine learning methods. Its computational cost, however, makes it unscalable and impractical for applications involvi...
Michael P. Holmes, Alexander G. Gray, Charles Lee ...
With the advent of high throughput technologies, feature selection has become increasingly important in a wide range of scientific disciplines. We propose a new feature selection ...